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Ant Colony Optimization Algorithm Based on Immune Strategy

Authors: Xiaoxia Zheng; Yang Fu;

Ant Colony Optimization Algorithm Based on Immune Strategy

Abstract

Ant Colony Optimization (ACO) is inspired by the ability of ant colonies to find shortest paths between their nest and a food source. The paper proposed a modified ACO based on artificial immune strategy. The mechanism of the vaccination, antibody diversity and clonal deletion theory in artificial immune system are introduced to improve the ways of artificial ants search solution space and the elite ant's capability. Also it can solve the conflict between the diversity of the solutions searched by ant colony and the convergence speed. The simulation results by examples of traveling salesman problem(TSP) show that adding immune strategy to ants group can find better solution in shorter time than ACO.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Average
Average
Average
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